The role of today's mobile devices—e.g., smart phones, mobile tablets, and wearable computing devices—has expanded dramatically as these devices have proliferated. People do far more on their mobile devices than just make phone calls or access the Internet. New and useful applications for mobile devices are being developed at rapid pace, and many of these applications use location-detection services to perform tasks. These devices communicate through radio waves over dedicated and varying frequencies or dedicated segments of the electromagnetic spectrum. The ability to estimate the relative distance between mobile devices is important for a number of wireless device applications that require location awareness.
Global Positioning System (GPS) solutions do not perform well indoors and provide somewhat weak location-detection precision. Another location-detection service being deployed is Wi-Fi fingerprint, but this technique uses a Received Signal Strength Indication (RSSI) that provides low spatial resolution. An additional inconvenience for Wi-Fi fingerprint technology is the need for a previous calibration phase, which must be performed whenever the physical topology changes significantly. Moreover, hardware-implemented solutions, such as the manipulation of physical layer (PHY) signal properties—e.g., through signal phases of antennas and round-trip time ends—require all new hardware to be developed or managed. Location-detection services should focus on procedures that enhance accuracy beyond the RSSI barrier and then can operate effectively indoors without having to reconfigure complex PHY layers.
If location-detection services use contention-based wireless technologies (e.g., Wi-Fi), performance degradation occurs in dense deployment scenarios due to the many nodes vying or transmitting for limited frequency bandwidth. For example, a large number of mobile devices in the same geographical area may have to compete to gain access to one or more radio frequency (RF) channels.